Identification of biomarkers related to CD8+ T cell infiltration with gene co-expression network in clear cell renal cell carcinoma.
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ABSTRACT:
SUBMITTER: Lin J
PROVIDER: S-EPMC7066925 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Lung squamous cell carcinoma (LSCC) is one of the most common types of lung cancer in adults worldwide. With the development of modern medicine, cancer treatment that harnesses the power of the immune system might be particularly effective for treating LSCC. In this research, LSCC expression data, which quantify the cellular composition of immune cells, were analyzed by weighted gene coexpression network analysis (WGCNA) and a deconvolution algorithm based on the Gene Expression Omnibus (GEO) database, and the results indicated a close relationship between LSCC and CD8+ T cells. Six hub genes (SYT3, METTL8, HSPB3, GFM1, ERLIN2, and CLCN2) were verified by gene-gene network and protein-protein interaction (PPI) network analyses. We found that the six hub genes were increased in cancer tissues and were closely correlated with cancer development and progression. After immune correlation analysis, METTL8 was selected as a prognostic biomarker. Finally, we found that the METTL8 levels were increased in multiple lung cancer cell lines and LSCC tissues. METTL8 inhibition could clearly induce G1 cell cycle arrest and suppress proliferation. Therefore, METTL8, which is related to CD8+ T cell infiltration, might be identified as a potential biomarker and gene therapy target in LSCC.
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Project description:Cytotoxic T cells expressing cell surface CD8 played a key role in anti-cancer immunotherapy, including kidney renal clear cell carcinoma (KIRC). Here we set out to comprehensively analyze and evaluate the significance of CD8+ T cell-related markers for patients with KIRC. We checked immune cell response in KIRC and identified cell type-specific markers and related pathways in the tumor-infiltrating CD8+ T (TIL-CD8T) cells. We used these markers to explore their prognostic signatures in TIL-CD8+ T by evaluating their prognostic efficacy and group differences at various levels. Through pan-cancer analysis, 12 of 63 up-regulated and 162 of 396 down-regulated genes in CD8+ T cells were found to be significantly correlated with the survival prognosis. Based on our highly integrated multi-platform analyses across multiple datasets, we constructed a 6-gene risk scoring model specific to TIL-CD8T. In this model, high TIL-CD8 sig score was corresponding to a higher incidence frequency of copy number variation and drug sensitivity to sorafenib. Moreover, the prognosis of patients with the same or similar immune checkpoint gene levels could be distinguished from each other by TIL-CD8 sig score.
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Project description:BackgroundImmune checkpoint blockade (ICB) therapy can be effective against clear cell renal cell carcinoma (ccRCC), but many patients show no benefit. Tumor-derived pericytes (TDPs) may promote tumor progression by influencing T cells and are an immunotherapy target; however, they may comprise functionally distinct subtypes. We aimed to identify markers of tumor-promoting TDPs and develop TDP-targeting strategies to enhance ICB therapy effectiveness against ccRCC.MethodsWe analyzed the relationship between endosialin (EN) expression and cytotoxic T-lymphocyte (CTL) infiltration in ccRCC tumor samples using flow cytometry and in a ccRCC-bearing mice inhibited for EN via knockout or antibody-mediated blockade. The function of ENhigh TDPs in CTL infiltration and tumor progression was analyzed using RNA-sequencing (RNA-seq) data from ccRCC tissue-derived TDPs and single-cell RNA-seq (scRNA-seq) data from an online database. The role of EN in TDP proliferation and migration and in CTL infiltration was examined in vitro. Finally, we examined the anti-tumor effect of combined anti-EN and anti-programmed death 1 (PD-1) antibodies in ccRCC-bearing mice.ResultsHigh EN expression was associated with low CTL infiltration in ccRCC tissues, and inhibition of EN significantly increased CTL infiltration in ccRCC-bearing mice. RNA-seq and scRNA-seq analyses indicated that high EN expression represented the TDP activation state. EN promoted TDP proliferation and migration and impeded CTL infiltration in vitro. Finally, combined treatment with anti-EN and anti-PD-1 antibodies synergistically enhanced anti-tumor efficacy.ConclusionENhigh TDPs are in an activated state and inhibit CTL infiltration into ccRCC tissues. Combined treatment with anti-EN and anti-PD-1 antibodies may improve ICB therapy effectiveness against ccRCC.
| S-EPMC10198862 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer whose prognostic is affected by the tumor progression associated with complex gene interactions. However, there is currently no available molecular markers associated with ccRCC progression and used or clinical application. In our study, microarray data of 101 ccRCC samples and 95 normal kidney samples were analyzed and 2,425 differentially expressed genes (DEGs) were screened. Weighted gene co-expression network analysis (WGCNA) was then conducted and 11 co-expressed gene modules were identified. Module preservation analysis revealed that two modules (red and black) were found to be most stable. In addition, Pearson's correlation analysis identified the module most relevant to pathological stage(patho-module) (r = 0.44, p = 3e-07). Functional enrichment analysis showed that biological processes of the patho-module focused on cell cycle and cell division related biological process and pathway. In addition, 29 network hub genes highly related to ccRCC progression were identified from the stage module. These 29 hub genes were subsequently validated using 2 other independent datasets including GSE53757 (n = 72) and TCGA (n = 530), and the results indicated that all hub genes were significantly positive correlated with the 4 stages of ccRCC progression. Kaplan-Meier survival curve showed that patients with higher expression of each hub gene had significantly lower overall survival rate and disease-free survival rate, indicating that all hub genes could act as prognosis and recurrence/progression biomarkers of ccRCC. In summary, we identified 29 molecular markers correlated with different pathological stages of ccRCC. They may have important clinical implications for improving risk stratification, therapeutic decision and prognosis prediction in ccRCC patients.
| S-EPMC5915556 | biostudies-literature
Project description:The malignant phenotypes of cancer are defined not only by its intrinsic tumor cells but also by the tumor infiltrating immune cells (TIICs) recruited to the cancer microenvironment. Clear cell renal cell carcinoma (ccRCC) immune microenvironment plays an important role in the tumorigenesis. This research investigated the characteristics of immune cell invasion of renal cell carcinoma and provided clues for future clinical implementation. Retrospectively, ccRCC gene expression was analyzed with appropriate clinicopathological data from the Cancer Genome Atlas (TCGA) and GEO database up to December 2019. The CIBERSORT algorithm, meta-analysis, principal component analysis (PCA), Single-Sample Gene Set Enrichment Analysis (ssGSEA) and hierarchical agglomerative clustering were used to measure and evaluate the respective proportions of 22 cell types of immune infiltration using normalized gene expression data. We also focused on evaluating the association with TIICs subpopulations and clinical features and molecular subtypes. TIICs subpopulation, especially Macrophages subgroup, T follicular helper (Tfh) cells and CD8 T cells, all contribute to tumorigenesis. Unsupervised clustering analysis revealed that there existed two distinct TIICs subgroups with different survival patterns. TIICs are extensively involved in the pathogenesis and development of the ccRCC. Characterizing the composition of TIICs influences the metabolism of tumors, activity, level, stage, and survival of patients. Collectively, the TIIC analysis has the potential to assist in the assessment and selection of ccRCC prognosis and treatment.
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Project description:Background: Kidney renal clear cell carcinoma (KIRC) has the highest invasion, mortality and metastasis of the renal cell carcinomas and seriously affects patient's quality of life. However, the composition of the immune microenvironment and regulatory mechanisms at transcriptomic level such as ceRNA of KIRC are still unclear. Methods: We constructed a ceRNA network associated with KIRC by analyzing the long non-coding RNA (lncRNA), miRNA and mRNA expression data of 506 tumor tissue samples and 71 normal adjacent tissue samples downloaded from The Cancer Genome Atlas (TCGA) database. In addition, we estimated the proportion of 22 immune cell types in these samples through "The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts." Based on the ceRNA network and immune cells screened by univariate Cox analysis and Lasso regression, two nomograms were constructed to predict the prognosis of patients with KIRC. Receiver operating characteristic curves (ROC) and calibration curves were employed to assess the discrimination and accuracy of the nomograms. Consequently, co-expression analysis was carried out to explore the relationship between each prognostic gene in a Cox proportional hazards regression model of ceRNA and each survival-related immune cell in a Cox proportional hazards regression model of immune cell types to reveal the potential regulatory mechanism. Results: We established a ceRNA network consisting of 12 lncRNAs, 25 miRNAs and 136 mRNAs. Two nomograms containing seven prognostic genes and two immune cells, respectively, were successfully constructed. Both ROC [area under curves (AUCs) of 1, 3, and 5-year survival in the nomogram based on ceRNA network: 0.779, 0.747, and 0.772; AUCs of 1, 3, and 5-year survivals in nomogram based on immune cells: 0.603, 0.642, and 0.607] and calibration curves indicated good accuracy and clinical application value of both models. Through co-correlation analysis between ceRNA and immune cells, we found both LINC00894 and KIAA1324 were positively correlated with follicular helper T (Tfh) cells and negatively correlated with resting mast cells. Conclusion: Based on the ceRNA network and tumor-infiltrating immune cells, we constructed two nomograms to predict the survival of KIRC patients and demonstrated their value in improving the personalized management of KIRC.
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Project description:The tumor microenvironment (TME) exerts a high impact on tumor biology and immunotherapy. The heterogeneous phenotypes and the clinical significance of CD8+ T cells in TME have not been fully elucidated. Here, a comprehensive immunogenomic analysis based on multi-omics data was performed to investigate the clinical significance and tumor heterogeneity between CD8+ T cell-related molecular clusters. We identified two distinct molecular clusters of ccRCC (C1 and C2) in TCGA and validated in E-MTAB-1980 cohorts. The C1 cluster was characterized by unfavorable prognosis, increased expression levels of CD8+ T cell exhaustion markers, high immune infiltration levels as well as more immune escape mechanisms. The C2 cluster was featured by favorable prognosis, elevated expression levels of CD8+ T cell effector markers, low load of copy number loss and low frequency of 9p21.3 deletion. Moreover, the effect of molecular classifications on Nivolumab therapeutic efficacy in the CheckMate 025 cohort was examined, and the C2 cluster exhibited a better prognosis. Taken together, we determine two CD8+ T cell-related molecular clusters in ccRCC, and provide new insights for evaluating the functions of CD8+ T cells. Our molecular classification is a potential strategy for prognostic prediction and immunotherapeutic guidance for ccRCC patients.
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Project description:Neutrophil cytoplasmic factor 1/2/4 (NCF1/2/4) belongs to the NADPH oxidase complex, which is a cytoplasmic component, and its polymorphism is the main factor related to autoimmune diseases, which is probably caused by the regulation of peroxide. They also play a role in tumor growth and metastasis. This research is aimed at evaluating the biological function and prognostic role of NCF1, NCF2, and NCF4 genes in kidney renal clear cell carcinoma (KIRC) by using multiple online bioinformatics website, including Oncomine, GEPIA, UALCAN, Kaplan–Meier Plotter, TIMER, TISIDB, cBioPortal, LinkedOmics, GeneMANIA, and DAVID databases. The mRNA levels of NCFs were higher in KIRC tissues than in normal tissues. The overexpression of NCFs was significantly correlated with advanced pathological grades and individual cancer stages in KIRC. Meanwhile, the expressions of NCFs played an important role in the tumorigenesis and progression of KIRC. Prognostic value analysis suggested that high transcription levels of NCF1/4 were associated with poor overall survival in KIRC patients. In addition, results from the LinkedOmics database showed that the KEGG pathway related to NCFs mainly focused on immune activation and immune regulation function. NCF genetic alterations, including copy number amplification, missense mutation, and deep deletion, could be found through the cBioPortal database. Further, NCF expression was significantly correlated with infiltration levels of various immune cells as well as immune signatures. Protein-protein interaction network and enrichment analysis of NCF1/2/4 in KIRC showed that NCF coexpressed genes mainly associated with diverse immune marker sets showed significance. Overall, these results indicated that NCFs could be prognostic biomarkers as well as effective targets for diagnosis in KIRC.
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Project description:ObjectivesTumor necrosis receptor super family (TNFRSF) plays an important role in regulating the function of CD8+ T cells. In this study, we explored the clinical significance and immune profile of TNFRSF9+ CD8+ T cells in clear cell renal cell carcinoma (ccRCC).MethodsThe infiltration of immune cells was determined by immunohistochemistry in ZS cohort from our hospital and their prognostic value was further determined by Cox regression. Functional status of CD8+ T cells in ccRCC was determined by flow cytometry in 29 fresh tumor samples. In silico analysis on a TCGA cohort and other datasets was performed to further demonstrate our findings.ResultsHigh TNFRSF9+ CD8+ T cells infiltration was associated with inferior overall survival in ZS cohort (p = .0016) and TCGA-KIRC cohort (p = .018). TNFRSF9+ CD8+ T cells expressed higher exhaustion markers (PD-1, TIM-3, CTLA-4, and TIGIT), and effector markers (IFN-γ, GZMB, CD107a, and Ki-67), than their TNFRSF9 negative counterparts. In silico analysis indicated the expression of TNFRSF9 was significantly correlated with IFNG, GZMK, MKI-67, PDCD1, HAVCR2, TIGIT, and CTLA-4 in CD8+ T cells. However, higher TNFRSF9 signature was correlated with larger tumor size shrinkage (p = .003) and better progression-free survival (p = .012) in patients treated with nivolumab but not everolimus.ConclusionTNFRSF9+ CD8+ T cells, which possessed both exhaustion and effector phenotype, were identified as an adverse prognosticator in ccRCC. These cells enrichment was associated with better immunotherapy response which indicated these cells potentially be crucial in immunotherapy.
| S-EPMC7595587 | biostudies-literature
Project description:Searching for reliable indicators for evaluating prognosis diagnosed with clear cell renal cell carcinoma (ccRCC) is crucial for improving clinical therapies. However, current researches have looked mainly at the prognostic value of a single intratumoral indicator, neglecting tumor-infiltrating immune cells (TIICs) in the microenvironment. This study examined whether the integration of Ring finger protein 43 (RNF43) expression and CD163+ tumor-associated macrophage (TAM) infiltration in combination with clinical indexes forecast ccRCC patient outcome with relatively high accuracy. Firstly, the expression of RNF43 and CD163 were detected with immunohistochemistry. Totally, 346 ccRCC patients were random separated evenly into training and validation datasets to make further analyses. We found that RNF43 expression was negatively correlated with infiltration level of CD163+ TAM in ccRCC, which was closely associated with the TNM stage and outcome of these patients. The multiple regression analysis demonstrated that RNF43, CD163, and TNM stage could function as independent risk factors in overall survival (OS) and progression-free survival (PFS) prediction of ccRCC. Furthermore, a better postoperative prognosis index for ccRCC patients was obtained by combining RNF43 and CD163+ TAMs, which assessed with time-dependent C-index analyses and a nomogram. Consequently, combining RNF43 and CD163+ TAMs along with TNM stage acquired robust accuracy in forecasting outcome of patients with ccRCC. In conclusion, combining intratumoral RNF43 expression, CD163+ TAM infiltration, and TNM stage could significantly enhance the veracity in forecasting postoperative outcomes.
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